DocumentCode
416778
Title
Combinatorial optimization algorithm for permutation using multi-agents and reinforcement learning
Author
Kobayashi, Yoko ; Aiyoshi, Eitaro
Author_Institution
Tepco Syst. Corp., Tokyo, Japan
Volume
3
fYear
2003
fDate
4-6 Aug. 2003
Firstpage
2916
Abstract
This paper deals with combinatorial optimization of permutation type using multi-agents algorithm (MAA). In order to improve optimization capability, we introduced the reinforcement learning and several processes into this MAA. Optimization capability of this algorithm was compared in traveling salesman problem and it provided better optimization results than the conventional MAA and genetic algorithm.
Keywords
genetic algorithms; learning (artificial intelligence); multi-agent systems; travelling salesman problems; combinatorial optimization algorithm; genetic algorithm; multiagents algorithm; permutation; reinforcement learning; traveling salesman problem;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE 2003 Annual Conference
Conference_Location
Fukui, Japan
Print_ISBN
0-7803-8352-4
Type
conf
Filename
1323843
Link To Document